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Authors: Sarunya Kanjanawattana and Masaomi Kimura

Affiliation: Shibaura Institute of Technology, Japan

ISBN: 978-989-758-158-8

Keyword(s): Relationship, OCR, Ontology, Triple, Edit Distance, Dependency Parser.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Engineering ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Acquisition ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Symbolic Systems

Abstract: A two dimensional graph is a powerful method for representing a set of objects that usually appears in many sources of literature. Numerous efforts have been made to discover image semantics based on contents of literature. However, conventional methods have not been fully able to satisfy users because a wide variety of techniques are being developed, and each is very useful for enhancing system capabilities in their own way. In this paper, we have developed a method to automatically extract relationships from graphs on the basic of their captions and image content, particularly from graph titles. Furthermore, we improved our idea by applying several technologies such as ontology and a dependency parser. The relationships discovered in a graph are presented in the form of a triple (subject, predicate, object). Our objectives are to find implicit and explicit information in the graph and reduce the semantic gap between an image and literature context. Accuracy was manually estimated to identify the most reliable triple. Based on our results, we concluded that the accuracy via our method was acceptable. Therefore, our method is dependable and worthy of future development. (More)

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Paper citation in several formats:
Kanjanawattana, S. and Kimura, M. (2015). A Proposal for a Method of Graph Ontology by Automatically Extracting Relationships between Captions and X- and Y-axis Titles.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015) ISBN 978-989-758-158-8, pages 231-238. DOI: 10.5220/0005602102310238

@conference{keod15,
author={Sarunya Kanjanawattana. and Masaomi Kimura.},
title={A Proposal for a Method of Graph Ontology by Automatically Extracting Relationships between Captions and X- and Y-axis Titles},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)},
year={2015},
pages={231-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005602102310238},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2015)
TI - A Proposal for a Method of Graph Ontology by Automatically Extracting Relationships between Captions and X- and Y-axis Titles
SN - 978-989-758-158-8
AU - Kanjanawattana, S.
AU - Kimura, M.
PY - 2015
SP - 231
EP - 238
DO - 10.5220/0005602102310238

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